Distribution plays an essential role in the supply chain system. One of the most challenging problems in distribution is determining vehicle routes. The purpose of this research is to propose the Improved Ant Colony Optimization (IACO) Algorithm for solving the Vehicle Routing Problem with Time Windows (VRPTW) to minimize distance while taking into account the destination customer's vehicle capacity and time windows. The proposed IACO algorithm is based on the conventional ACO algorithm but with the addition of local search and mutation processes. Numerical experiments were performed to ensure that the resulting route did not violate the VRPTW constraint. Furthermore, this study compares the performance of IACO with other metaheuristic algorithms. It analyzes the effect of iteration on distance, the number of routes, and computation time. The numerical experiments show that the proposed IACO algorithm can minimize the distance.